{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example Code for \"Ultra-efficient causal deep learning for Dynamic CSA-AKI Detection Using Minimal Variables\"\n",
    "\n",
    "REACT (Real-time Evaluation and Anticipation with Causal disTillation): a causal deep learning approach that\n",
    "combines the universal approximation abilities of neural networks with\n",
    "causal discovery to develop REACT, a reliable and generalizable\n",
    "model to predict a patient's risk of developing CSA-AKI within the next\n",
    "48 hours."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import Utils and Set Up Environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from run_example_utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "device = \"cuda\"\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "np.random.seed(42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Example Dataset\n",
    "\n",
    "The study incorporated data from five large-scale general hospitals: The\n",
    "First and Third Medical Centers of the Chinese PLA General Hospital in\n",
    "Beijing, China, were used for the derivation of the predictive model and\n",
    "internal validation(from 2000 to 2021); For model external tests, we\n",
    "utilized the Sixth and Seventh Medical Centers of the Chinese PLA\n",
    "General Hospital, along with the Nanjing Drum Tower Hospital in Nanjing,\n",
    "China (from 2000 to 2023). **Our cohort, comprising 54,896 patients,** was\n",
    "selected from a pool of approximately 6.19 million individuals with 8.3\n",
    "million visits treated at five major general hospitals.\n",
    "\n",
    "Data underpinning this study are under restricted access and are not\n",
    "freely available as they contain patients’ data, and specific clearance\n",
    "from the ethics committee is required in each center. **So we release a example dataset with several patients with simulated data for reproducing our work.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/ssd/2/cyx/UNN/REACT/medical_pred_main.py:569: UserWarning: No train_val dataset.\n",
      "  warnings.warn(\"No train_val dataset.\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dy feat num =  87\n",
      "St feat num =  10\n",
      "Dy dim =  2\n",
      "St dim =  2\n",
      "T length =  168\n",
      "Pred dim =  [2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]\n"
     ]
    }
   ],
   "source": [
    "opt_gc_pred, log, test_dataset = prepare_example_model(OmegaConf.load(opj(os.getcwd(), \"example/example.yaml\")), device=device, mode=\"test\")\n",
    "load_dir = opj(os.getcwd(), \"model_weights/6_var\")\n",
    "pred_model = Example_Prediction(opt_gc_pred, log, device=device)\n",
    "pred_model.load_model(load_dir, test_dataset.dynamic_items, test_dataset.static_items)\n",
    "patient_data_list = test_dataset.patient_data_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetch Example Patient from the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "example_patient_index = 3\n",
    "patient_data = patient_data_list[example_patient_index]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show Basic Information\n",
    "SEX: -1 for male, -2 for female."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SEX: -2\n",
      "AGE: 69.0\n"
     ]
    }
   ],
   "source": [
    "for item_index, (item_name) in enumerate(patient_data.basic_info_items[:2]):\n",
    "    print(f\"{item_name}: {patient_data.basic_info[item_index]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Show Observed Time-series of Six Variables\n",
    "\n",
    "The causal variables ultimately included in REACT\n",
    "are blood urea nitrogen, uric acid, Lactate Dehydrogenase, Creatine\n",
    "Kinase Isoenzyme, and age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sample num:  165\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 1500x700 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "example_sample_index = len(patient_data.data_dynamic) // 2\n",
    "draw_patient_example(patient_data, example_sample_index)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dynamic Prediction Curve v.s. CSA-AKI Label\n",
    "\n",
    "The threshold is determined by setting the false positive rate to 0.67."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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s6oUNB/XLt7arqqFVDb5AzCiX00qyBqrkIc1ps+qqU0v0vQWTlBPVdX6iWfgAAAAAhj7GuQAAgKRV4W3Ryj01EWtnj85RYdSIk6HMYbVo/oR8zRubq/f21Ohf2ypiQt1dNU26940tmpSfETHKxWG1aFphxgBXPLSNykrV1MIMvbOrun3N20qIDgAAACQzOtEBAEDSenHjIXXIjGW3GrpsalHC6ulPdqtF54/L012XTOt07EggZGpjeeTYkelFGYxy6YHorn9vJ7PpAQAAACQPQnQAAJCUdlY3an1UaLxgQoEyU5J7A0iH1aKrTi3RbedPVG6q84THMsqlZ9KdkSF6A53oAAAAQFIjRAcAAEnHNNtmgXeU5rDpookFCapo4I3PTdMPL5qs88bmdXq/w2rRtALPAFeVHDJckRMRGecCAAAAJDdCdAAAkHQOeVu0+0hTxNqlUwqVYh9eo0ucNqs+f1qpvnXueGVFbYY5uzRLDhu/CvZE9DiXBl9Qpml2cTQAAACAoY4rJwAAkHSqG/0Rt9OcNs0bm5ugahJvUn6GfnTRFF0wPk9ZbodOKfLoylOKE13WkBUdogfDploCoQRVAwAAAKC/2U5+CAAAwNDiD4Ujbntcdtksw7t3IMVu1WdnlOqzM0oTXcqQl+6M/RXa2xqQ28Gv1gAAAEAyGt5XkwAAIClFh+h2K7/yoO/YrRa5o0YDeVuDCaoGAAAAQH/jihIAACSdQFSI7iBERx+LHuni9bG5KAAAAJCsuKIEAABJJ7oT3WE1ElQJklWGK3J0i7eVEB0AAABIVoToAAAg6fiDjHNB/0qP7kRnnAsAAACQtLiiBAAASSdmnIuNX3nQtzKc0SE6negAAABAsuKKEgAAJJ3YcS78yoO+xTgXAAAAYPjgihIAACSd6BCdcS7oa9Ebizb4GOcCAAAAJCuuKAEAQNKJGedCiI4+Fh2i04kOAAAAJC+uKAEAQNLxh8yI23Sio69Fj3Np9AUVCptdHA0AAABgKOOKEgAAJJ1AkE509K/ojUVNtQXpAAAAAJIPV5QAACDpMBMd/S3VaZPFiFzz+hjpAgAAACQjrigBAEDSiZmJbjO6OBLoGYthKM0ZOdKFuegAAABAciJEBwAASSe6E51xLugP0SNdvK2McwEAAACSEVeUAAAg6TDOBQMhwxUdotOJDgAAACQjrigBAEDSiRnnQoiOfpDuihzn0kCIDgAAACSlIX9F2draqhtvvFGZmZkqKirSAw880OWxf/3rXzVlyhSlpaVp3rx5+vDDDwewUgAAMFAY54KBENOJzsaiAAAAQFIa8leUd9xxhz744AMtW7ZMjz76qBYvXqxnn3025rhNmzbpmmuu0Q9/+EOtW7dOM2fO1OWXX67m5uYEVA0AAPpL2DQVCJkRa4xzQX9gJjoAAAAwPAzpK8qmpiY9/vjjeuihhzRr1ixdeeWVuvPOO/XII4/EHPvaa69p2rRpuu666zRu3Djde++9qqio0ObNmxNQOQAA6C/BqABdohMd/SMjapwLM9EBAACA5DSkryjXrVunQCCguXPntq/NmzdPq1evVjgc+TbunJwcbdq0SStWrFA4HNaSJUuUkZGhcePGDXTZAACgH0WPcpEkh21I/8qDQYqNRQEAAIDhwXbyQwav8vJy5ebmyuFwtK8VFBSotbVVNTU1ysvLa1+/+uqr9eKLL2revHmyWq2yWCx6+eWXlZWV1elj+3w++Xy+9tter7f/vhAAANBnojcVlRjngv4RHaK3BsPyB8O8aAMAAAAkmSH9G35zc7OcTmfE2rHbHQNwSaqpqVFFRYUeeeQRrV69Wtddd51uuOEGVVVVdfrY9957rzweT/tHaWlp/3wRAACgT3XaiU6Ijn4QHaJLbC4KAAAAJKMhfUXpcrliwvJjt91ud8T697//fZ1yyim69dZbNXv2bP32t79VamqqlixZ0ulj//CHP1R9fX37x/79+/vniwAAAH0quhPdYkhWi5GgapDMXDaL7FH/bTHSBQAAAEg+QzpELy4uVnV1tYLBYPtaRUWFUlJSlJmZGXHs2rVrNWPGjPbbFotFM2bM0N69ezt9bKfTqYyMjIgPAAAw+EV3otOFjv5iGEZMN3pDa7CLowEAAAAMVUP6qnLmzJmy2+1atWpV+9q7776rOXPmyGKJ/NJGjBihzZs3R6xt27ZNY8aMGZBaAQDAwPAHI0N05qGjP6WzuSgAAACQ9Ib0xqJut1uLFi3SLbfcoiVLlujgwYO6//7720e0VFRUyOPxKCUlRV/96ld1/fXXa86cOTr77LP1+OOPa+/evVq0aFGCvwoAANCX6ETHQMpwRf46zUx0AAAAIPkM6RBdkh588EF9/etf1/z58+XxeLR48WJdddVVkqSioiItWbJE119/va6++mo1Njbq5z//uQ4cOKCZM2dq2bJlys/PT/BXAAAA+lL0THSHjRAd/SfDGd2JzjgXAAAAINkM+RDd7XZr6dKlWrp0acx9pmlG3L7xxht14403DlRpAAAgAfyhyJ//jHNBf4qdiU4nOgAAAJBsuKoEAABJhXEuGEiMcwEAAACSH1eVAAAgqcSMcyFERz+K7kRnnAsAAACQfLiqBAAASSU6RLdbjQRVguEgNkQPxIwUBAAAADC0EaIDAICk4g/SiY6Bk+GMHOcSDJtqCYQSVA0AAACA/sBVJQAASCqxnej8uoP+kx7ViS4x0gUAAABINlxVAgCApBKzsaiNX3fQf+xWi1Ls1og1NhcFAAAAkgtXlQAAIKlEh+h0oqO/ZbgiR7p4WwnRAQAAgGTCVSUAAEgqMZ3ohOjoZ9GbizYwzgUAAABIKlxVAgCApBIImRG3CdHR3zKckSE6negAAABAcuGqEgAAJBXGuWCgRXeiMxMdAAAASC5cVQIAgKTiDzLOBQMrdiY641wAAACAZMJVJQAASCqB6JnoNn7dQf9Kj+5EZ5wLAAAAkFS4qgQAAEklOkS3W4wEVYLhgpnoAAAAQHIjRAcAAEkleiY6nejob9HjXBp9QYVNs4ujAQAAAAw1XFUCAICkEtOJzkx09LPojUVNtQXpAAAAAJIDV5UAACBpmKYZ24lOiI5+lua0KXpoECNdAAAAgOTBVSUAAEgaIdNUOGqKBp3o6G8Ww1B61EgXQnQAAAAgeXBVCQAAkoY/GI5ZoxMdAyF2c1HGuQAAAADJgqtKAACQNAKh2M0c2VgUAyF6LrrXRyc6AAAAkCy4qgQAAEkjeh66xDgXDAzGuQAAAADJi6tKAACQNDoN0S3RWz4CfY9xLgAAAEDyIkQHAABJIxAVojusFhkGITr6X8w4FzrRAQAAgKRBiA4AAJJGdCc6m4pioESPc2kgRAcAAACSBleWAAAgaQSCkSG63UoXOgZG7MaijHMBAAAAkgUhOgAASBr+MJ3oSIzomegtgVDMeCEAAAAAQxNXlgAAIGnEdKLb+FUHAyMjapyLxEgXAAAAIFlwZQkAAJIGM9GRKCl2q2yWyPFBjHQBAAAAkgNXlgAAIGlEh+h2QnQMEMMwYuei04kOAAAAJAWuLAEAQNIIhMyI23SiYyBFj3QhRAcAAACSA1eWAAAgadCJjkSK3lzU28o4FwAAACAZcGUJAACShj/ITHQkTjrjXAAAAICkxJUlAABIGgE2FkUCxYxz8RGiAwAAAMmAK0sAAJA0ose5OGxGgirBcBS7sSjjXAAAAIBkQIgOAACSRnQnOjPRMZCiZ6I3MM4FAAAASApcWQIAgKQR04lOiI4BFNuJHpBpmgmqBgAAAEBf4coSAAAkDTrRkUjRM9EDYVOtUZvdAgAAABh6bCc/RBozZowMo3szRXft2tWrggAAAHqKTnQkUnpUJ7rU1o2eYrcmoBoAAAAAfaVbIfrdd9/d7RAdAAAgUfxBOtGROA6rRSl2q1oCofa1zRVeFaS7ElgVAAAAgN7qVoj+pS99STbbyQ/dv39/rwsCAADoqUAocv40negYaEUZLu2qaWq//cKGgxqdnaoxOakJrAoAAABAb3TryvJTn/qUfD7fCY/57W9/q1NOOaVPigIAAOiJ6HEudKJjoF00sSDidsg09fiqXfK2BhJUEQAAAIDe6taV5YYNG7Rw4UJ5vd6Y+/bv36+LL75Yt9xyiy6//PI+LxAAAKC7Ymai2wjRMbBOHZGpiybmR6zVtwb0xOrdCoXNLs4CAAAAMJh168ryvffe0+HDh7VgwQLV1NS0r//2t7/V9OnTVVZWpn/84x/64x//2G+FAgAAnEyAjUUxCHxqWrEm5qVHrO2obtQLGw4mqCIAAAAAvdGtK8uRI0dqxYoVstlsmjdvnlasWKGFCxfqG9/4hm688UZt2rRJl156aX/XCgAA0KWwaSoYjp6JzsboGHhWi6EbzhytrBR7xPryHVX6YP+RBFUFAAAAoKe63Z6VnZ2tZcuWacyYMTrvvPNUXl6ulStX6sEHH5Tb7e7PGgEAAE4qugtdYiY6EifdaddNZ4+VzRL5Qs4f1+7VwfrmBFUFAAAAoCfiurJ0u936+9//rmuvvVbV1dVyOp39VRcAAEBc/MHYEJ1xLkikUVmp+vzM0oi1QMjUYyt3q9kfTFBVAAAAAOJl685BP/nJTyJujxs3ToZh6Pzzz9e3vvUt2WzHH+auu+7q2woBAAC6obNOdDYWRaLNHZOrvbXNWrG7un2tusmnpWv26Oa542QxGDkEAAAADHbdCtGXL18eszZ58mRJ0jvvvNO+ZhgGIToAAEgIP+NcMEh9dkaJDtQ1a2/t8TEumyq8em1bhS6dXJTAygAAAAB0R49D9M6Ul5f3qhgAAICe8ociNxW1WQy6fDEo2K0W3XTWWP3nsq1q9B0f4/LypnKNyU7VpPyMBFYHAAAA4GR63Z7l8/n01FNP6ROf+IRGjhzZFzUBAADELXqcC13oGEyy3A595Ywx6viyjilpyft7VNfiT1RZAAAAALqhx1eXK1as0Ne+9jUVFhbq2muv1f79+/XLX/6yD0sDAADovuhxLoToGGwm5qfrk9NGRKw1+oJ6YvVuhcJmF2cBAAAASLRujXM5Zu/evXryySf15JNPateuXcrMzJTX69VTTz2lz33uc/1VIwAAwEn5g5EhuoMQHYPQwkkF2l3TqI0V3va1XTVN+tvGg7rq1JIEVgYAAACgK926ulyyZInmz5+vsWPH6re//a0uvvhivfbaa6qsrJTFYtG0adP6u04AAIATCoSjQ3TmoWPwsRiGrpszWjluR8T6srIqfXSwNkFVAQAAADiRbnWi33jjjRo/fryefPJJXXvttf1dEwAAQNxiOtFtdKJjcHI7bLrxrLF68M1tCnYY4/LHD/aqOCNF+ekuhU1T5d4W7axu0s6aRh2sa5HDZtH43DRNzk/X+Nx0/hsHAAAABki3QvQnnnhCTz31lK6//nr9v//3/3T55Zfryiuv1MUXXxz3EwaDQT3++OO67LLLNHLkSN1111167rnnNGvWLD300EPKzs6O+zEBAACYiY6hZGSWW5+dUaKnPtrfvtYaDOs37+1UbppTu2qa1BIIxZy3r7ZZy8qqZLMYGpOTqsn5GZqUn66RWW5ZDN59AQAAAPSHbl1dXn/99Xr11Vd16NAh3X333dq5c6euvPJK5ebmKhwO680331QgEOjWE373u9/VT3/6U9XW1upvf/ub7rvvPl133XXat2+fvvWtb/XqiwEAAMNXIMRMdAwt54zJ1RkjIxtIKht92lTh7TRA7ygYNlV2uFF/33RI9y/fprtf3aSN5fX9WS4AAAAwbBmmaZonPyzWgQMH9Oc//1lPPfWUPvroI+Xk5OjLX/6yHnzwwROeV1BQoL/97W8666yzdM0116ixsVEvvviiNm3apLlz56q+fnD+8u/1euXxeFRWVqbMzMxElwMAAKK8vPmQXtlS0X77tOJM3XjW2ARWBJycLxjS/cu3qdzb2iePt2BCvj49fYRsFl5EAgAAAE4mFAopGAyquLj4hMf1+LfrkpIS3XHHHVq7dq22bdumb37zm3r11VdPel5zc7MKCgoUDAb1yiuv6JOf/KQkKRwOy2br1nQZAACAGNGd6IxzwVDgtFl101lj5epivnmO26E5I7N19cxSfWJKocbmpMpygqkty8qq9OCb23W40ddPFQMAAADDT4870XvqkksuUXp6ujwej/7whz9o//79qqio0De/+U0VFhbqmWeeGchyuo1OdAAABrdnPtqvt3cdbr99zphcfXHWyARWBHTf3tomvbjhkHyhsEZluTUuN01jc1KVmeKIObYlEFLZ4QZtrWrQ1kqvqjoJzF02i74wa6ROL2W/IQAAAKAr3e1EH/DW78cff1zf+ta3tHbtWi1ZskT5+fn6n//5H+Xn5+vRRx8d6HIAAECSCISZiY6ha1RWqr513oRuHZtit+rUEZk6dUSmTNPUO7uq9fz6AwqGj/fGtAbD+v37e7StqkGfm1EqRxed7gAAAABObsB/m37qqaf08MMP6+OPP9Y111wjSfrZz36mZ599Vrm5uXE/Xmtrq2688UZlZmaqqKhIDzzwQJfHbtiwQfPmzVNKSopOOeUULV++vMdfBwAAGFz8wehxLieYeQEkCcMwdN64PH1v/iTlpzlj7l+5p0b/tWyrqpsY7wIAAAD0VNwh+uzZs7Vhw4YeP+E999yjYDDY4/Oj3XHHHfrggw+0bNkyPfroo1q8eLGeffbZmOPq6+u1cOFCTZ06VRs2bNBVV12lK6+8UlVVVX1WCwAASBx/1Ex0Om8xnJRkuvX9CyfrzFGx41sqGlr1y7e2q7KhbzYvBQAAAIabuK8uy8vLZbVae/yE11xzjX72s5+prKxMfr+/x48jSU1NTXr88cf10EMPadasWbryyit155136pFHHok5dunSpUpLS9OvfvUrjR8/XosXL9aECRP0wQcf9KoGAAAwOERvLMo4Fww3TptVXz59tK47fVTMf/91LQH98q3tOlTfkqDqAAAAgKEr7pno1113nS699FJ96Utf0ujRo+VyuWLuP5FXXnlFe/fu1e9///tO7w+FQt2uZd26dQoEApo7d2772rx583TPPfcoHA7LYjl+8fDmm2/qiiuuiHgBYM2aNd1+LgAAMLjFdKITomOYOmNUjkZlp+p3q3bpkPd493mDL6iH3t6ub547QaWZ7gRWCAAAAAwtcYfoTz/9tKxWq/785z/H3GcYxklD9K7C854oLy9Xbm6uHA5H+1pBQYFaW1tVU1OjvLy89vVdu3bpjDPO0Ne+9jW9+OKLGj16tB544AGdc845nT62z+eTz3d8dqTX6+2zugEAQN+LDtHthOgYxgrSXbrt/Il69N0d2lvb3L7e5A/pf94u063zxmt0dmoCKwQAAACGjrhD9N27d/fqCc8///xend9Rc3OznM7IDZSO3e4YgEtSY2Oj7rvvPt1222165ZVX9NRTT+niiy/W1q1bVVpaGvPY9957rxYvXtxntQIAgP4VCNKJDnSU6rDpm+dO0K9W7NCumqb29ZZASA+/U6avnzNe43PTElghAAAAMDTEHaJLbR3gjzzyiLZs2aJQKKTJkyfrpptu0oQJE0567pgxY2QYRpf379q1q9t1uFyumLD82G23O/ItqjabTaeddlp7MH7aaafptdde0//93//pRz/6Ucxj//CHP9R3v/vd9tter7fTsB0AAAwO/rAZcZsQHZBS7FbdOm+8fvPeLm0/3NC+7guG9ei7O3Tz3LGalJ+RwAoBAACAwS/uEP2dd97RZZddplNOOUVnn322QqGQ3nrrLT388MP617/+1eV4lGN+/OMfR9wOBoPauXOnfv/73+unP/1pXLUUFxerurpawWBQNlvbl1JRUaGUlBRlZmZGHFtUVKTJkydHrE2cOFH79+/v9LGdTmdMlzsAABi8ojvRGecCtHHarLrlnHF6fOUuba48PqLQHwrrVyt26rbzJmpMDqNdAAAAgK7EHaLffvvt+uY3v6l77703Yv0HP/iB7rjjDr333nsnPH/RokWdrp911lm6//77deONN3a7lpkzZ8put2vVqlWaN2+eJOndd9/VnDlzIjYVPfb4b731VsTa1q1bdc0113T7+QAAwOAVs7GojRAdOMZhteirZ4/VktW7tb68vn09GDa1dM1u/fCiKXLarAmsEAAAABi84r663Lhxo77yla/ErN944436+OOPe1zI1KlTtWbNmrjOcbvdWrRokW655RatWbNGL7zwgu6//37ddtttktq60ltaWiRJt9xyi9avX68f//jH2rFjh+666y7t2rVLX/rSl3pcMwAAGBxM01SAjUWBE7JbLbrxrLGaVZIVsV7d5Ndz6w4kqCoAAABg8Iu7E3306NF6//33Y+afr169WoWFhSc9/+23345Za2ho0MMPP6zp06fHW44efPBBff3rX9f8+fPl8Xi0ePFiXXXVVZLaRrgsWbJE119/vUaNGqV//vOf+va3v6377rtPU6ZM0csvv6zi4uK4nxMAAAwuwbApM2qNmehALKvF0KI5o1XX4o/YbPS9PTU6ZUSmTinyJLA6AAAAYHCKO0S/8847dcstt2jr1q0644wzJEmrVq3Sww8/rJ///OcnPf+CCy6IWXM4HJozZ44ee+yxeMuR2+3W0qVLtXTp0pj7TDPycvqcc87R2rVr434OAAAwuEWPcpEku7XrjcyB4cxqMXTd6aN17xtb5Ouwl8Cf1u7VjxZOUbrTnsDqAAAAgMEn7hD9+uuvlyQ9/PDDeuCBB+RyuTRp0iT97ne/0+c+97mTnh8Ox17kAgAA9Eb0KBeJTnTgRHLTnPrMqSX604f72tcafEE99eE+3XTWWBkGL0IBAAAAx3QrRF+wYIH+/Oc/q6CgQE8++aS++MUvtofpPdHS0qI//OEP2rJli0KhkCZPnqzPf/7zysnJ6fFjAgCA4csf7CREZ2NR4ITOHp2j9eX12thho9F1h+q1et8RnTWK38sBAACAY7p1dblq1SqVl5dLkm644QZ5vd4eP+HGjRs1YcIE/exnP9PevXu1d+9e/fznP9eUKVO0efPmHj8uAAAYvqLHuRiSrHTSAidkGIaumTVSaY7IvppnP96vmiZfgqoCAAAABp9udaJffPHFmjt3rgoKCmSapk4//XRZrdZOj921a9cJH+u2227TwoUL9dhjj8lma3v6YDCom266Sd/5znf02muvxfklAACA4S46RHfYLIyjALohw2XXF2eN1GOrjv8O3xoM6/8+2KtvnzdBFv4/AgAAALoXoj/99NN69dVXVVdXpxtuuEG33367PB5Pj55w5cqVevTRR9sDdEmy2Wz6wQ9+oNNPP71HjwkAAIa3QChyM3HmoQPdN6M4U2eOytbqvUfa13ZUN2pZWZUumliQwMoAAACAwaFbIbrT6dQVV1zRfvsLX/iCnE5nj56wqKhIO3bs0KRJkyLWd+zYoYyMjB49JgAAGN6iO9HthOhAXD47o1Rlhxt1pNnfvvbSpkOaXpihwoyUBFYGAAAAJF7cV5iLFi3qcYAuSbfccotuuukm/e53v9OGDRu0YcMGPfbYY/rqV7+qm266qcePCwAAhq9A9DgXQnQgLil2q758+ih1HN4SDJt6ceOhhNUEAAAADBbd6kTvS9/73vfU1NSk73//+zpypO0towUFBfrud7+r22+/faDLAQAASYBOdKD3JuSla/6EfC0rq2pfW19er101jRqbk5bAygAAAIDEGvArTMMw9OMf/1jV1dWqqKhQXV2dysvLdccdd8hi4YIXAADELxCM3VgUQPw+MaVIaY7IPpsXNx6SaZpdnAEAAAAkv7g70b1eb5ezy1944QX927/920kfY9u2bVq/fr1aW1tjfiG/7rrr4i0JAAAMczGd6BajiyMBnEiK3apLJhfqufUH2td2VDdqS6VXUws9CawMAAAASJy4Q/QLLrhAr732mnJzc9vXdu3apW9+85t6/fXX5ff7T3C29Itf/EK33367MjMz5fFE/iJuGAYhOgAAiFvMTHQ60YEemzc2V8t2VKm2wyajL248pMkFGbIYvEAFAACA4SfuK8xx48bpnHPO0b59++Tz+XTXXXdp2rRpamlp0dq1a096/n/+53/qwQcf1JEjR7R79+6Ij127dvXoiwAAAMNbdCc6G4sCPWe3WnT5lKKItQP1LfrwQG2CKgIAAAASK+5O9GeeeUbf+c53NHfuXDmdToVCIT355JP63Oc+163zW1padMUVV8RdKAAAQFfYWBToW2eMytbr2ytV0dDavvbSpnKdVpwlK+OSAAAAMMzEfYVpGIYeeugh3Xbbbdq/f7+WLFnS7QBdkr785S/rf//3f+N9WgAAgC75ozcWJUQHesViGPr09BERa9VNPr23pzpBFQEAAACJ061O9DFjxsjoZP6hYRi6/PLLVVhY2L7W2UiW+fPnt5/v9/v13nvv6ZlnntGYMWNktVojjl22bFlcXwAAAEAgHLlROSE60HunFHk0OjtVe440ta+9sqVcZ47MYd8BAAAADCvdCtF//OMf9+pJLrjggojbCxcu7NXjAQAAdBTdic44F6D3DMPQFdNH6KG3y9rXvK1BvbmzShdPKjzBmQAAAEBy6VaIvmjRoi7va21t1YYNGzRx4kR5PJ5Oj7n77rt7Vh0AAEA3BNhYFOgXE/LSNbUgQ5srve1r/9pWqXljcuV2xL29EgAAADAkxX2FuXnzZp111ll67733VFdXp9NOO01nnnmmSkpKtHz58v6oEQAA4IRiNhZl1ATQZz4VNRu9JRDSv7ZVJqgaAAAAYODFfYV56623auzYsZo4caJ+97vfqa6uTuXl5frRj36k22+/vT9qBAAAOCE60YH+U5rp1uySrIi1N3dUqa7Fn6CKAAAAgIEV9xXm6tWrdc899yg3N1cvvPCCrrrqKhUUFOiaa67R1q1b+6NGAACAE4rpRLfGbogOoOc+Oa1Ilg7/WwXCpl7fTjc6AAAAhoe4Q/TMzExVVFRo//79WrlypT75yU9Kkj766CMVFBTEXcCBAwcUDodPfiAAAEAXojcWpRMd6Ft5aS6dPTo3Ym3Frmp5WwMJqef17ZX60cvr9eCb23SkmY54AAAA9K+4dwO6/vrr9elPf1pOp1NjxozRxRdfrF//+tf63ve+p5/+9KdxFzB16lStW7dOY8aMiftcAAAASQqEQnL5W2UPBRSw2mW30IneFX9VlUK+1rjPszpdcuTn90NFQ9Nw/D5eMqlAK/dUK2y23T7WjX7VqSU9fsyefB8P1bVo+ceH5HV75G0N6sk1e/Sd8yf2uAYAAADgZOIO0X/+859rzpw52rt3r774xS/KarVq5MiReuqpp9q70qPNnz9fhtH5xWxzc7OuueYapaSkSJKWLVsWb0kAAGCYCjU3q371al3x1mvKaPEev2Nzto4sWCDPmWfK6nYnrsBBxl9VpZ0/Wdzj88fddfeQDYD70nD9PmanOnXWqBy9t6emfe3dXdVaOKlA6U573I/Xm+/jlyT94czPqt7t0Y7qRh2oa1ZJJv+vAwAAoH/EHaJL0pVXXhlx+7LLLjvh8VOnTtWvf/1rzZ07VxdddFHEfStWrNAZZ5yh7OzsnpQCAACGqcbNm3Xg8cdk+v1Ki76z9ogqn3tWVX9/USU3fVVpU6cmosRBpyed0315frIYzt/HiycVatXemvZudH8orGVlVbpienHcj9Xb74M9dHyUzNs7D+ua2aN69XgAAABAV7oVoo8dO1Zr1qxRTk6OxowZ02VXuSTt2rUrZu1///d/de211+rmm29WWVmZfvGLXygvL0+SdP/99+u2227T2LFje/glAACA4aZx82bt/9Wj7be7moBuBgLa/6tHVfr1bxCkA30gN82pOSOztXrvkfa1t3ce1oUTCpTm7FF/Tp9Ys/+IrjilWKmOxNUAAACA5NWt3zLvvvtupaW19Xj9+Mc/7tETzZ07Vx9++KHuvfdezZgxQz/5yU9000039eixAADA8BVqbtaBxx9ru2GaJz7YNCXD0IHHH9OEn93DaBegD1wyqVDv7z2iY//3+YJhvbmjSp+cNiJhNQVCplbtqdGFEwsSVgMAAACSV7dC9EWLFrX/+a9//avuu+8+TZ48Oe4ns9vtuuuuu/T5z39eN998s5YuXapgMBj34wAAgOGrfvVqmX5/908wTZl+v+rfX63sC+b3X2HAMJGf7tLpI7O1Zt/xbvQ3d1RpwYR8uRPYCf7OrsOaPyFflhO8axYAAADoia7e/dylFStWyGbr3S/HkydP1ltvvaUvfelLOvvss9s3FQUAADgR0zR15K03e3TukTfflHmyznUA3XLJpEJ1jKpbg2G9ueNwwuqRpOomv7ZUeE9+IAAAABCnuNPwb3zjG7r66qt1yy23aNSoUXK5XBH3n3feeZ2e19raqhUrVqi+vl7z5s1Tfn6+br75Zt18883t9z/zzDO67rrrevBlAACArpimqapGn9x2q9Jd9kSX0yuhpiYFqqt7dG6gulqhpibZ0mK2IQUQp8IMl04rydKHB2rb15bvqNL8CflKsVsHpIaidJecnhQdrG9pX3tr52FNK/IMyPMDAABg+Ig7RP/pT38qSe3hd0eGYSgUCsWsb9myRZ/4xCdUU1Mj0zQVCoV05513avHixe3H1NfX64YbbiBEBwCgD5mmqcdX7da6Q3WyWw19fmapzh6dm+iyeizs8/X+fEJ0oE9cOrkwIkRvCYT01s4qXTq5aECef3JBhuzFefrTh/va17ZUenW4sVV5aa4TnAkAAADEJ+5xLuFwuMuPzgJ0Sfr2t7+thQsXqra2VvX19frFL36hBx54QFdffXWX5wAAgN7bW9usdYfqJLVtvPentfv0/r6axBbVCxanM6HnAzhuhCdFM4szI9aWlVWpNTAwv99Pzk/X6aXZEZ3vpqR3dvXs3SoAAABAV+IO0Xvi/fff1/e//33ZbDZZrVbdcssteuONN/Taa6/pC1/4gsLh8ECUAQDAsFPhbY24bUr6wwd7te5gXULq6S1raqrsuT3rpLfn5sqamtrHFQHD26WTCyNuN/tDemfXwMxGz0ixy2Gz6OzRORHrK/fUyB/k+gIAAAB9Z0BC9JycHJWVlUWsnXnmmfrHP/6hV199Vddcc42CweBAlAIAwLBS1+KPWQub0pL3d2tL5dDbgM8wDGWff0GPzs2+4AIZhnHyAwF0W0mmW6dGzSB/o6xKvuDAvdv03LG5EZuctgRC+mD/kU6PDYVNVXhbFQqzyTAAAAC6b0BC9JtvvlnXX3+97r//fh06dKh9/eyzz9bf//53vfLKK7r00ksHohQAAIaVupZAp+vBsKnfrtypndWNA1xR73nOPFOGwyF1NxA3DBkOhzxnnNm/hQHD1KVTImegN/qCWrVn4MZG5aW5NKUgI2LtrZ2HZZrHg/JAKKw3d1Tp//vHBv3sX5v1H69siJjnDgAAAJzIgITo3//+97V48WI999xz2rNnT8R9F1xwgVasWKGMjIzOTwYAAD3WWSf6MYGQqV+t2KH9tc0DWFHvWd1uldz01bYbJwvSj95f8tWvyep293NlwPA0MsutaYWRv8svK6sa0G7v88flRdw+WN+iXTVNCoVNrdxTrZ/8c5OeXXdADb62d796W4N6YvVuPb5ql7ytnb/YCAAAABzToxC9vr5e//u//6vbbrtN1dXVeumll7Rz584TnnPLLbdo5cqVmjt3bsx906dP14oVKyK61AEAQO/VRYVDmSn2iNutwbAeebdM5d6WgSyr19KmTlXp178hw26XKamr6ceG3a7Sb9yqtClTBrI8YNhZOLEg4nZNs18fHRy4Tu8phRnKTXVErP11w0Hd86/N+uPafart4l05Hx+s08/+tVlr9h2J6FwHAAAAOoo7RN+4caMmTJigJUuW6Fe/+pW8Xq+ef/55zZw5U2+99VaviikoKDj5QQAAoNuix7lcfdpITY+aX9zkD+nhd3boQN3Q6khPmzpVE352j2rPvUQNKekR99lzc1Xw2c9qwj0/J0DvwOp0JfT8ZMH3Mda43DSNzo58t8fr2ytPGEz35ffRYhg6d2xkN/qeI02qavSd9HGa/SEtXbNHv125S/VdhO0AAAAY3gwzzpaLBQsW6Nxzz9XixYuVnp6udevWaezYsfr+97+v5cuX6/333++vWhPK6/XK4/GorKxMmZmZiS4HAICTCoTC+n8vfByx9qOLpigvzalfrdip7YcbIu6zWQxdMb1YF4zPG1IbcL606ZBe3VIuZ9AnRzCgKSNz9eVzpw6pr2Eg+auqFPK1xn2e1emSIz+/Hyoamvg+xvr4YK0eX7U7Yu2b88ZrckHXYxtP9n18aVO5NlXUt98uzXTrmtkjO/0+NvmD+v/+sUGBUNeXN+Nz0zRjRKb+ubVCjf5gzP0pdqu+OGukZpVkdfkYAAAASB6hUEjBYFDFxcUnPM4W7wOvWbNGjz32WMz6zTffrEceeSTehwMAAP2kvpM5v5kpdtmtFt08d6weeWeHdh9par8vGDb13PoD2lLp1ZdPH6V0lz3m/MHIHwpLhiGf3SWf3SXDnUqAfgLJGuAONL6PsU4dkam8NKcOd+j+fn175QlD9BN9HwOhsFZ/eESt6bnta/OnlyiltPNzUh02zSnN1nudbGpamunWp6eP0OT8dBmGodNHZukvH+/XhwfqIo5rCYS0ZPVupTltmpiXHvM4AAAAGJ7iHueSl5en7du3x6y/9957jGMBAGAQiR5L4LBalGK3SpKcNqu+fs64mPELkrS50qufv75Fmzt0fw5mgVDkRHSHdUD2TQcQxWIYunBCZMC9tapB+3s4KmpzhVetweP/fxuSZhafuEP8ookFctmO/xtQkO7UjWeN0Z0LJmlKQUb7C2zpTru+cuZY3XjWGKU7I/uKTEkvby7vUc0AAABITnF3on//+9/XTTfdpB/96EcKh8NatmyZli5dql/+8pe65557uvUYb7zxhtasWaNAIBAzJ/Guu+6KtyQAANCJ2hZ/xO3MFHtEh7bbYdNt503US5sO6Y2yqohjG3xBPbpip+aPz9enp4+QfRAH0/6oEH0w1wokuzNG5ejlzeVq8B0flfL69krdcMaYuB/rw6iNScfnpcmTcuJ3yOSnu3T7/Elaf6hehekunTLCI8sJ3plyWnGWJuSm65mP9+vDA8efb2d1o3ZWN2pcblrcdQMAACD5xB2i33zzzRoxYoT++7//W263W3fccYcmTZqkxx57TJ///OdPev7tt9+uhx56SDNmzFBGRuRbOw3DIEQHAKCPRHeiZ3YSPtmtFl15aokmF2To/z7YI29r5Izg5TuqtLXKq0smF+q04ixZLYNvTAqd6MDg4bBadP74PL206Xgn90cHavWpaSOUm+rs9uP4Q2FtOBT5bphZJ+lCP6YoI0VFGSndfq40p03XzRmlXTWNEZsx/2tbhcblju/24wAAACB5xR2iHzx4UJ/61Kf0qU99qkdP+MQTT2jp0qW69tpre3Q+AADonrqYEN3R5bFTCjL0w4um6I8f7NXGCm/EfeXeVv3+/T36u/uQFkws0NmjcuSwDZ6g2h+kEx0YTM4dm6fXtla2v0skbErLy6r0uZml3X6MTRX1Ee8yMSTNKM7s40qPs1ksunBCgZ5bf6B9bWOFVwfrW1Ts6X4gDwAAgOQU91XmyJEjdd555+nRRx/V4cOH435Cm82mM844I+7zAABAfOqixrmcbAxCutOum+eO0+dmlsrWScd5TbNff/l4v+56ZaNe2VKuRl+wk0cZeP5Q5Gg4OtGBxEp12HTOmNyItZV7auL6N+OjA5GjXCbkpSujnzc7njsmR26HNWLt9e2V/fqcAAAAGBrivsrcunWrLrvsMj3xxBMqLi7WRRddpMcff1y1tbUnP1nSrbfeqrvvvltNTU1xFwsAALovnk70YwzD0Pnj8nTHgslddl82+oN6eXO57nplo5au2aOVe6pV0+Trk5p7ImacyyDqkgeGq/kT8tXxtTh/KKx3dnWvAccXDGljeeQ7YmaVZPZhdZ1z2qy6YFzkxqhr9x9J6L9vAAAAGBzivsqcMGGCfvCDH+iDDz7Q9u3bddlll+nJJ59USUmJPvnJT570/LfeekvPPfecMjMzVVJSorFjx0Z8AACAvhHdiZ4ZRxdnsSdF379wsm48c4xGZrk7PcYfCmvNviP649p9uvvVTbr7lY36wwd79f7eGtU2+zs9pz9EbyxKJzqQeNluh2aXZkesvbXjcMz/r53ZVOGNOM5i9O8ol47OG5cX8W9I2FTMxssAAAAYfuKeid6Ry+VSSkqK0tPTZbFY1NzcfNJzrr/+el1//fW9eVoAAHASYdNUfWtUJ7o7vlEIFsPQaSVZmlmcqbLDjfrX9kptqfR2eXxNs181e2u0am+NJGlyfro+M6Mkrg3+eiI6lLNbB9/mp8BwdNHEfK3Zd6T9dqM/qNV7anTuuLwTnvdh1CiXiXnpSnf27yiXY9KcbaNolu84Hpyv3F2tT0wuVHo/j5MBAADA4BV3iL537149//zzeu6557R69WrNmTNHV199tR5//HEVFRWd9PxFixb1qFAAANB9Da1BhSNHhSvTdfJxLp0xDEMT89M1MT9dB+qa9fr2Sn14oDbm8aNtrWrQva9v0Xnj8nTZlCK5Hb167b5LMeNc6EQHBoVij1tTCzK0ucOLb2+UVWrumFxZO9l3QWob5bKpvD5ibVZJVr/WGW3BhHy9tbOq/d+4QNjUmzsP61PTRgxoHQAAABg84r6aHTNmjGbMmKEvfOEL+uMf/6hRo0ad9JwFCxbo+eefV2ZmpubPny/D6LpDbNmyZfGWBAAAotS1Ro5TsRhSuqv3IXZJplvXnzFGV0wv1sbyem0/3KCyw41q9He+YWDYlN7ccVgf7K/Vp6eN0Fmjc2Q5we8BPcE4F2DwunBiQUSIXt3k10cHa3V61KiXYzaU1yvQ4RU6iyGdOiKzv8uMkOV2aM7IbK3ee7yL/u2dh3XRxAKl2K0nOBMAAADJKu6r6S1btmjSpElxnXP++efL4WjrfrvgggvifUoAABCnuubIUS4el71Pw+sst0PnjsvTuePyFDZNlXtbVXa4oT1UbwmEIo5v9AX1pw/36d3d1frcjFKNyUnts1oCwehxLoTowGAxMS9NI7Pc2ld7fOzjP7dWaFZJVqf/Jn0UNcplUn6G0pz98y6WE1k4sUDv7z2iY3F+SyCkFburddHEggGvBQAAAInXrd9If/KTn+h73/ue3G63nn766RMee9ddd8Ws3X333Z3+GQAA9I+66HnoKT0b5dIdFsNQsSdFxZ4UXTA+X75gSP/aVqnXt1cqGDXzZV9tsx54c5vmj8/XVacWn/Ddad0RNs2IrlVJctgI0YHBwjAMXTKpUI+t2tW+Vu5t1cby+pgO85ZASJsqIvddGOhRLscUZqTo1BEerTt0fLTMsrIqnT8ujxfqAAAAhqFuhejLly/Xt7/9bbndbi1fvrzL4wzD6DRE7ygQCGjJkiVat26dWltbZZqRF75PPPFEd0oCAAAnUNcSOc4lM2XgNsRz2qz65LQROmtUjp7fcEDrD9XHHLN8R5Vcdosun9q7GcPBUOxgdgIuYHA5ZYRHhekuVTS0tq/9c2uFTinyRLyQtrG8PuKFN6thaMYIz4DW2tHCSYURIbq3NaA1+45o7pjchNUEAACAxOh2iH7M0qVLVVJSIosl8gI1FApp3bp1J32sm2++WX/5y1+0cOFCeTyJ+6UYAIBkVt8ycJ3oXclNc+prZ4/Tlkqvnv14vyobfRH3v7KlQvlpLs0Z2fls5O6InocuMRMdGGwshqGLJxfoyTV729f21jZrW1WDJhdktK99GDXKZXJBer9tSNwdo7NTNTEvTdsPN7av/Wt7Zb/s7QAAAIDBrUcbi1ZUVCgvLy9ifffu3Zo3b56am5u7OLPNX/7yF73wwgu68MIL431qAADQTYnsRI82pSBDP1w4RW/uOKy/bTiojr3jf1y7V9luh8blpvXosTsL0elEBwaf2SXZenlTuWqaj//b9Nq2ivYQvSUQ0pbKyFEupyVolEtHCycVavvhHe23Dzf6tO5g3aCoDQAAAAOnW1eZjz/+uMaOHauxY8fKNE2dfvrp7bePfcyZM0dTp0496WN5PB6NGNG7t24DAIATq4vqRPckMESXJJvFoosmFuizM0oi1oNhU4+t3KXqqC717grQiQ4MCVaLoYWTIjfl3H64Ubtq2rq81x+qixjlYrMYOrUo8e9anZyfrpLMlIi117ZVxIykBAAAQHLrVif6okWL5HA4FA6H9ZWvfEW33357xCgWwzCUmpqqBQsWnPSx/uM//kO33XabfvWrX2ns2LG93lAMAABEMk0zJkTPSsA4l86cPz5fVY0+vbXzcPtaoz+oX723Q7dfMCnu0Q3RnehWw5DVwu8WwGB05qgcvbKlQvUdNj7+59YKff2c8Z2McslI6CiXYwzD0MWTCvXE6t3ta/vrWrS1qkFTOoyiAQAAQHLr1m+mdrtd1113naS2cS7nnHOOjhw5ovz8fEnSypUrNWvWLDmdzk7Pt1gs7WH5sa6NiRMndnpsKBSK7ysAAAARWgKhmHA50Z3oHV11aokON/q0ucPohsoGn363ere+cc74uEJwfzDy67RbCdCBwcputejCifl6fv3B9rVNFV5tP9ygrZUNEcfOKskc4Oq6NrM4U3mpTh1uOv6OmX9tqyREBwAAGEbibu/weDwaM2aMvvjFL+q//uu/JEnXXnutTNPUSy+9pGnTpsWc03FjUgAA0L+iu9AlyeMaPCG61WLohjPH6BdvbtMhb2v7+raqBj3z8X594bTSbr9TLXqci8PGKBdgMDtnTK7+ubVCTf7jjTNPrNqtkBk5yuWUoswEVNc5i2HookkF+vOH+9rXth9u0J4jTRqdnZrAygAAADBQ4r7S/OY3v6mrrrpK99xzT/vajh079KlPfUq33nprp+ecf/757R9Lly7VrFmzItbOP/98nXrqqXr44Yd7/pUAAABJsSF6mtM26DbbTLFbdcs545XujHw9f8Xuai0rq+r240R33DMPHRjcnDar5o/Pj1hr9Acjbk8tyFCK3TqQZZ3UGSOzlRH1YuS/tlUmqBoAAAAMtLg70T/66CM9+eSTstuP/xJpsVh02223acaMGZ2es3LlSpWVlUlSe4iekRH59setW7fqtddei7cctba26tZbb9Vzzz2nlJQUfe9739Ptt99+wnP27Nmj6dOn66WXXtIFF1wQ93MCADCY1bX4I25nDqJRLh1lux26ee44PfTWdgU6bCj4t40HNTE/XaWZ7pM+RnSIPtheLAAQ67xxeXp9e6Vag7EbA0vSrNKsAa7o5OxWixaMz9cLG4+Poll/qE4V3lYVZrgSWBkAAAAGQtwh+siRI/XGG29o7NixEesrVqxQYWFhp+e43W79+Mc/lmmaMk1T//Vf/yWr9Xh3ybGNSf/zP/8z3nJ0xx136IMPPtCyZcu0d+9eLVq0SKNGjdJnP/vZLs/5+te/rqamprifCwCAoaDjpn2SlDmIRrlEG52dqi/PGR2xaV/YlP60dp++N3/SSeejx4xzIUQHBj23w6Zzx+V12slttxiaXuhJQFUnd87YXP1zW4VaAm2jaExJb5RV6trZoxJbGAAAAPpd3CH6v//7v+vGG2/UypUrNXv2bEnSunXr9Ic//EGPPvpop+fMmDFDu3btkiTNnz9fzz//vLKyet9h0tTUpMcff1yvvPKKZs2apVmzZmnTpk165JFHugzR//jHP6qhoaHT+wAASAa1zdGd6I4EVdI9s0qydKi+Ra9urWhf21/XrDd3VOnCiQUnPNcfMiNu04kODA0LxufrzR1VCkT9Pzy10CPXIBvlckyK3apzx+bqtQ7h//t7j+iyKUXKcg/uf2cBAADQO3FfaX7pS1/Siy++qPr6ev3qV7/S448/rrq6Ov3zn//U9ddff9Lzly9f3icButQW3gcCAc2dO7d9bd68eVq9erXC4di3h9bU1OjOO+/Ub37zmz55fgAABqPomeiDdZxLR5dMLlRheuRIhJc3l6u6yXfC8wJBOtGBoSjdZdc5o3Nj1meVZA58MXGYPz5f9g7vkAmZZlz7OAAAAGBo6tGV5iWXXKLnnntOGzdu1EcffaRnnnlG5557bpfHW61WVVW1/XJpsVhktVq7/IhHeXm5cnNz5XAc7/woKChQa2urampqYo7/7ne/q0WLFmnatGlxPQ8AAENJzDiXQd6JLrV1kH9x1siINX8orKc/2i/TNLs4i5nowFB24cQC2ToE0il2q6YXDc5RLseku+w6Oyr8X7G7Wo2+YBdnAAAAIBl0a5zLV77yFT300ENKT0/XV77ylRMe+8QTT8SsLVu2TNnZ2ZLaOtH7SnNzs5xOZ8Tasds+X2Tn2uuvv653331XGzdu7NZj+3y+iMfwer29rBYAgIFRG7WxqGcIdKJL0rjcNJ07Nlfv7KpuX9tS6dUH+2s1Z2R2p+fEzES3EaIDQ0WW26EvnT5Kz647IIshXT1zpJy2wTnKpaMFE/P17u7DOrYfsj8U1ju7DusTU4oSWxgAAAD6TbdC9I4dYCfqBuvK+eef3/7n3/3ud/rEJz6hiy++WDk5OXE/VkculysmLD922+12t6+1tLTo5ptv1qOPPqqUlJRuPfa9996rxYsX96o+AAAGmj8UVrM/FLGWNURCdEn69PRirT9UH9FN/9y6A5pSkKE0Z+yvLdGd6IxzAYaW00uzNbskS6Yki3HijYQHi9xUp2aXZGnN/tr2tTd3VGnBhPwh8SIAAAAA4tetEH3JkiWd/rknSktL9Ytf/ELXX3+9ZsyYoUsvvVSXXnqpzjrrLFks8V34FhcXq7q6WsFgUDZb25dSUVGhlJQUZWZmth/3/vvva9euXfrMZz4Tcf4nPvEJLVq0SL/+9a9jHvuHP/yhvvvd77bf9nq9Ki0tjas+AAAGWn1UF7okeYbAOJdjUuxWfX5mqR5btat9rdEf1PPrD+i6OaNjjo8d5zI0QjgAxxmGoaH2f+5FkwojQvQmf0gr99TogvH5CawKAAAA/aVbIfpPfvKTbj/gXXfddcL777nnHt1zzz2qra3V8uXL9cYbb2jRokWqqanRwoUL9fTTT3f7uWbOnCm73a5Vq1Zp3rx5kqR3331Xc+bMiQjkzzjjDJWVlUWcO2HCBD3++ONauHBhp4/tdDpjRsUAADDYRW8q6rJZlGIfWp2RM4ozNWNEptYdqmtfe3/fEc0Zma0pBRkRx9KJDiARij0pmlaYoU0Vx0c+vrG9UnNH5zJWCgAAIAl1K0TvOMc8FArp3Xff1YgRIzRz5kw5HA6tW7dO+/bt02WXXdbtJw4GgzIMQy6XS9nZ2dq9e7fWrVsXV/Fut1uLFi3SLbfcoiVLlujgwYO6//7727vlKyoq5PF4lJKSovHjx8ecX1xcrPx8ukUAAMkjOkQfKvPQo31uZom2H25QS+D4aJqnPtynf184NSKgipmJTogOYIBcPKkwIkSvbQno6Y/36UuzR8kYIqNpAAAA0D3dutJcvnx5+8eMGTP0ta99TXv27NFLL72k559/Xjt27NC3vvUtpaWlnfSxbrjhBk2cOFElJSX6+c9/rlAopDvvvFOHDh3S1q1b4/4CHnzwQc2ePVvz58/XrbfeqsWLF+uqq66SJBUVFcXV2Q4AwFBXFzXOJXMIjXLpKDPFoSumj4hYq2n26+XNhyLW/MHocS6E6AAGxrjcNI3Pjbz+Wb33iFbsru7iDAAAAAxV3epE7+j3v/+91q5d2z6DXGqbY3jLLbfotNNOO+n57777rnbt2qWFCxfqkksu0bx58zRr1ixZrT17q7nb7dbSpUu1dOnSmPtOtAlqTzZIBQBgsIvuRM8cop3okjR3TK7W7K/VzurG9rVlZVU6vTRbpVltG4jTiQ4gkb44a6T+a9lW+Tq8oPfsugMqzXRrVHZqAisDAABAX4r7SnPEiBF69dVXY9afe+45jR079qTnl5WV6cCBA7rhhhu0Y8cOfeUrX1F2drYuuugiLV68ON5yAABAB7Eh+tDsRJcki2Hoi6eNlM1yfCyCKemPH+5VKNz2Yrg/FPmiuJ1ZxAAGUEG6S1+aPSpiLRg29fjq3Wr0BRNUFQAAAPpa3J3o9913n66++mr9/e9/18yZM2WaptasWaMPPvhAL774Yrceo6ioSFdffbUuu+wyvf3223rhhRf0f//3f3rvvfd09913x/1FAACANrHjXIZuJ7okFWa4dMnkQr28ubx97UBdi5bvqNJFEwvoRAeQcKeVZGnBkSYtK6tqX6tt9uv37+/WN+aNl4X56AAAAENe3FeaV155pT7++GPNnDlTW7Zs0datW3X22Wdr/fr1uvDCC096/j/+8Q/deeedOuOMM5STk6M777xTaWlp+utf/6qampoefREAAKBNfWtUJ7praIfokrRwUoEK010Ray9vPqTqRp/8IWaiA0i8K6YXx8xH31rVoFe2lHdxBgAAAIYSw+zFcPDa2lplZGTIYrF0ewf6nJwcXXTRRbr44ot1ySWXqKSkpKdPP6C8Xq88Ho/KysqUmZmZ6HIAAIgRCpv6zl8/Uscf7N+/cLJKM90Jq6mv7Kpp1C/e3B7xtU3OT9eB+paIkQnfOneCJuWnD3yBAIa9+paA/nPZFnlbI8e4fH3uOE0r8iSoKgAAAJxIKBRSMBhUcXHxCY+Lu13LNE3dc889ys3NVV5envbu3asvf/nLuuWWW+Tz+U56fnV1tZ5++mndeOONQyZABwBgKGjwBRT9yngydKJL0ticNM0bmxuxtrWqIWbmMONcACSKJ8Wur5w5Vpao3qKla/aouunk10kAAAAYvOK+0vzpT3+qP/zhD/r9738vp9MpSVq0aJFee+013XHHHSc9v7sd6wAAID7Rm4raLIZSnXFvfzJofXp68UlnvNut/J4BIHHG56bp306J7GJqDoT08Ntl2l3TlKCqAAAA0Ftxh+i///3v9Zvf/Eaf/OQnZbG0nb5w4UItXbpUzzzzTJ8XCAAAuid6U1GPy55UG9ql2K36/MzSEx5DJzqARJs/Pl+nFWdGrNU0+/WLt7bpH5vLFQr3eJomAAAAEiTuK83KykqNGDEiZj0rK0uNjY19UhQAAIhfdCf6ybq2h6JTR2RqZlQ41ZHDRogOILEMw9C1s0epIN0ZsR42pX9sKdcv39qu6kbGuwAAAAwlcV9pXnjhhfrv//7v9tuGYaihoUE/+tGPNH/+/D4tDgAAdF9MJ3qKI0GV9K/PzShVit3a6X12OtEBDAIuu1XfnDdBY3NSY+7bfaRJ976xRav21Mg06UoHAAAYCuK+0nz00Uf10UcfqbCwUC0tLfr0pz+tkpIS7dmzRw8//HB/1AgAALphOHSiS22b910xvfOd0xnnAmCwyHI7dNt5E3X51KKYzUZ9wbD+sHavnli9W4fpSgcAABj04t5tLCsrS++//76WLVumLVu2KBgMatKkSbr44ovbZ6QDAICBN1xCdEmaOyZHa/Yf0c7q46PkDLVtpgoAg4XVYugTU4o0OT9DS9fsUXVTZGD+0cE6fXSwThPz0nT26FzNKM7kxUAAAIBBKO4Qfdq0afrrX/+qBQsWaMGCBf1REwAA6IHYED05x7lIksUwdM2skbr39S0KHt2kb3xemowk2kgVQPIYk5OqH1w4Wc+tP6CVe2pi7t9+uFHbDzcq5WOr5pRm6+wxOSrNdCegUgAAAHQm7hDdarXK7/ef/EAAADBgTNOMmYmezJ3oklSQ7tK3zp2glzYfktNm1WdO7XzECwAMBi67VdfOHqVphRn604f71OwPxRzTEgjp7V2H9fauwypMd2lMTqpGZrpVmuVWsSeFfR8AAAASJO4Q/fLLL9fChQv1yU9+UqNHj5bL5Yq4/6677uqz4gAAQPc0+UPtHdnHJHMn+jHjctN023kTE10GAHTbzOIsjc5O1evbKvX+viNqDsSG6ZJU0dCqioZWrVRb57rFkEZkpKg0y62iDJey3Q5lu53KdjuU6rDyThwAAIB+ZJhxbgk/f/78rh/MMLRs2bJeFzUYeb1eeTwelZWVKTMzM9HlAAAQ4UBds+57Y2v7bUPSL688TVZmhAPAoBUIhbXuUJ1W7qnRtqqGHj+Ow2pRltuuHLdTs0uzNGdktiyE6gAAACcVCoUUDAZVXHzidzbH3Ym+fPnyHhcFAAD6R33UPPR0l40AHQAGObvVotNLs3V6abaqm3xatadGq/bWxOxxcTL+UFiVDT5VNvi0udKrsCmdPTqnn6oGAAAYfrodov/hD3/Q888/L4fDoX/7t3/TF77whf6sCwAAxKE2KnDxuJJ/lAsAJJPcVKc+OW2ELptapN01Tdpb26T9tc3aV9usqkaf4nn78Af7jxCiAwAA9KFuhegPPfSQvve97+miiy5SIBDQokWLtH79ev385z/v7/oAAEA31LdGbiqaleSbigJAsrIYhsblpmlcblr7WmsgpAN1zdpb26yD9S2qafLpSEtAdc3+TsP16HcnAQAAoHe6FaL/+te/1u9+9ztdd911kqTnn39eN9xwg+655x42sAEAYBCIfuv/cNhUFACGC5fdqvF56Rqflx6xHgqbqm/xa2OFV898vL99vb6VEB0AAKAvWbpz0M6dO3XhhRe23/70pz+tpqYmlZeX91thAACg+6JDdA+d6ACQ9KwWQ9mpTk3KjwzXWwIh+UPhBFUFAACQfLrViR4MBmW3H78Yt9lsSklJUWtra78VBgDAcBU2TTX5ggqGTQVC4bbP4bCCIVPBsCmH1aL8dKdSHcd/jNe1MM4FAIarDFfsv/neloBy05wJqAYAACD5dHtjUQAA0P+2VTXo9+/vVoMveNJj0xw25ac7VZDuUk1TZIjuYZwLAAwbLptFDqslovu8vpUQHQAAoK90O0R/5plnlJGR0X47FArpr3/9q/Ly8iKOOzY3HQAAxO/Zdfu7FaBLUqM/qMaaoHbVNMXcl0knOgAMG4ZhyOOy63CTr32NuegAAAB9p1sh+siRI/XAAw9ErBUUFOiRRx6JWDMMgxAdAIAeCoVNVXj7ZlQaIToADC8ZKVEhegshOgAAQF/pVoi+Z8+efi4DAAA0+YMyu7jPZjHaPqwWNfuDCnd1oKRiT4qcNmu/1AgAGJw8UXPRvXSiAwAA9BlmogMAMEg0+CIDD0PS/VfMkMNqkWEY7euhsKnqJp+qGlpV2dj2uarRp+omnzwuu75w2sgBrhwAkGjRITrjXAAAAPoOIToAAIOEtzVyFnqqw9ZpR7nVYqgg3aWCdJdOGajiAACDGiE6AABA/7EkugAAANCmMWpD0TQnr3UDALonIyXyZwbjXAAAAPoOIToAAINE9DiXDBchOgCge2I60dlYFAAAoM8QogMAMEg0xHSi27s4EgCASNEhenMgpEAonKBqAAAAkgshOgAAg0RD1Ez0dMa5AAC6KcMV+8Irc9EBAAD6BiE6AACDRPQ4F0J0AEB3pditsluNiDXmogMAAPQNQnQAAAaJ6I1F0zvpKgQAoDOGYcTORSdEBwAA6BOE6AAADBLe6BCdTnQAQBzYXBQAAKB/EKIDADAImKapxqiOwTRCdABAHKLnojPOBQAAoG8QogMAMAj4gmEFwmbEWoaTcS4AgO5jnAsAAED/IEQHAGAQiN5UVJLSXXSiAwC6z5PCOBcAAID+QIgOAMAg0BA1D91uNeSw8mMaANB90eNc6EQHAADoG1ydAwAwCDS0RoboGU67DMNIUDUAgKEoepwLM9EBAAD6BiE6AACDQPQ4FzYVBQDEK3qcS5M/pEAonKBqAAAAkgchOgAAg0D0OJd0QnQAQJyiO9ElqYFudAAAgF4jRAcAYBCICdE7CUIAADiRFLtVNkvkKLD6qHFhAAAAiB8hOgAAg0B0pyCd6ACAeBmGEdONXt/qT1A1AAAAyYMQHQCAQSB2nAud6ACA+EXPRacTHQAAoPcI0QEAGAQaY8a50IkOAIhfRnQnegud6AAAAL1FiA4AwCDg9THOBQDQe9HjXLx0ogMAAPQaIToAAAkWCptq9oci1tIY5wIA6IHoTnRv1J4bAAAAiB8hOgAACRY9ykWSMuhEBwD0QOxMdEJ0AACA3iJEBwAgwRqiRrkYklIJ0QEAPRA9zoUQHQAAoPcI0QEASLCGqE70VKdNFsNIUDUAgKEsepxLoy+oYDicoGoAAACSAyE6AAAJFt2JzqaiAICeiu5El6QGNhcFAADoFUJ0AAASLDrcSGdTUQBAD6U6rLJZIt/NxEgXAACA3iFEBwAgwaLHudCJDgDoKcMwYka61LcQogMAAPQGIToAAAkWM87FRYgOAOi56BDdSyc6AABArxCiAwCQYI0xneiMcwEA9Fz0XHTGuQAAAPQOIToAAAnmjZmJTic6AKDnCNEBAAD6FiE6AAAJ1hg1ziWNEB0A0AsZKZE/R5iJDgAA0DuE6AAAJJBpmjEbi0bPsgUAIB4elyPiNjPRAQAAeocQHQCABGoNhhUMmxFrdKIDAHrDE7VBNeNcAAAAeocQHQCABGroJNhgJjoAoDc8KZHvaGr0BRWKesEWAAAA3TekQ/TW1lbdeOONyszMVFFRkR544IEuj3355Zc1c+ZMpaWl6dRTT9WLL744gJUCANC56FEuDqtFTps1QdUAAJJB9FgwU4x0AQAA6I0hHaLfcccd+uCDD7Rs2TI9+uijWrx4sZ599tmY49avX6+rrrpKX/nKV/Txxx/r5ptv1mc/+1mtW7cuAVUDAHBcQ9SmonShAwB6K9Vhk9UwItYI0QEAAHpuyF6pNzU16fHHH9crr7yiWbNmadasWdq0aZMeeeQRffazn4049k9/+pMWLFigb3/725Kk8ePH68UXX9QzzzyjGTNmJKJ8AAAkxXaip7uG7I9mAMAgYTEMZbhsqm05HpwzFx0AAKDnhuyV+rp16xQIBDR37tz2tXnz5umee+5ROByWxXK8yX7RokXy+/0xj1FfXz8gtQIA0JXG6BDdae/iSAAAui/DZSdEBwAA6CNDNkQvLy9Xbm6uHA5H+1pBQYFaW1tVU1OjvLy89vUpU6ZEnLtp0ya98cYbuuWWW7p8fJ/PJ5/P137b6/X2YfUAALSJfns941wAAH3Bk2KXao/fZpwLAABAzw3ZmejNzc1yOp0Ra8dudwy/o1VXV+szn/mMzjnnHF1xxRVdHnfvvffK4/G0f5SWlvZN4QAAdBDdiZ5GiA4A6AOeqM1F61sI0QEAAHpqyIboLpcrJiw/dtvtdnd6TmVlpRYsWKBwOKxnn302YuRLtB/+8Ieqr69v/9i/f3/fFQ8AwFHRM9EzXIxzAQD0XkyITic6AABAjw3Zdrfi4mJVV1crGAzKZmv7MioqKpSSkqLMzMyY4w8ePKgFCxZIkt58882IcS+dcTqdMZ3uAAD0tYaoUINOdABAX4h+UZYQHQAAoOeGbCf6zJkzZbfbtWrVqva1d999V3PmzInpMG9qatKll14qi8Wit956SyNGjBjocgEA6FR0JzobiwIA+oInJfLnCTPRAQAAem7Itru53W4tWrRIt9xyi5YsWaKDBw/q/vvv15IlSyS1daV7PB6lpKTo5z//uXbu3Kk333yz/T5JSklJkcfjSdSXAAAY5oLhsJoDoYi1DNeQ/dEMABhEose5NLQGFQqbslqMBFUEAAAwdA3ZTnRJevDBBzV79mzNnz9ft956qxYvXqyrrrpKklRUVKSnn35akvTcc8+ppaVFZ555poqKito/brvttkSWDwAY5qI3FZUY5wIA6BvRIbopqcFHNzoAAEBPDOkrdbfbraVLl2rp0qUx95mm2f7nrVu3DmRZAAB0S/QoF0NSqmNI/2gGAAwSqU6bLIYUPn5ZJG9rUJkpjsQVlcRCYVNrDxxRMGTq9JHZcliHdL8aAACIwpU6AAAJ0tAaGaKnOW2yGLzNHgDQexbDUIbLrrqW493n9S1+KcudwKqS158+3KvVe49IklbsrtZ3zp8oO0E6AABJg5/qAAAkSGPU2+rTGeUCAOhD0SNd6ltjx4ih91oCIb1/NECXpL21zfr7pkMJrAgAAPQ1QnQAABLEGzXOJd1p7+JIAADilxETovsTVElyO1jfIjNqbXlZlbYfbkhIPQAAoO8RogMAkCAxneguOtEBAH0nuhPdSyd6v9hf2xyzZkr6vw/2qiUQGviCAABAnyNEBwAgQaI3FqUTHQDQlzwp0Z3ogS6ORG8cqI8N0SWpttmvZ9ftH+BqAABAfyBEBwAgQTrbWBQAgL4SMxO9hRC9P3TWiX7M6r1HtO5g3cAVAwAA+gUhOgAACdIQNc4lg3EuAIA+FD0T3Usnep8LhMKqaGiNWDOijvnzh/v43gMAMMQRogMAkCDR41zSGOcCAOhDsTPRAwqb0VtgojcO1bco3OFbakj63MzSiGMa/UH9ce1emXzvAQAYsgjRAQBIANM01RgzE51OdABA34meiW5KMT970Dv761oibuelOXXu2FzNGJEZsb6pwqv39tQMYGUAAKAvEaIDAJAALYGQguHIjjRCdABAX0pz2mJGizAXvW8dqIuch16S6ZZhGPrirJExP9efW3dAhxt9A1keAADoI4ToAAAkQPQoF0lKZ5wLAKAPWQwjZi56PbO5+9T+qBC9NDNFUtsLGNfOHhVxnz8UZqwLAABDFCE6AAAJEB2iO20WOWz8WAYA9C02F+0/obCpQ/WR41xKMt3tf55e5NHc0TkR9++obtSHB2oHpD4AANB3eN84AKDbdlY3akN5nUZlp2rmiEwZRvSbxPtfayCkg/UtOuRtUbM/JEkyDLW/Xd1Q2w233aqCdJcK0l1KG4RjUhp8kSEGo1wAAP3Bk2LX/rrjt2tb/AmrJdlUNrQqEDWarbRDiC5Jn5lRom1VDappPv59f2HDQZ1SlMmL5wAADCFcsQMAumX9oTo9tnKXjl0qTi/M0JdOH92vAXVdi1/7apt1sL5FB+tbdKCuRdVN8c8STXPYVJDuVP7RUL0ow6USj1sZLltCXgiQpMbW6E1FGeUCAOh7nqhO9Hd2VuvMUTnKTXUmqKLkET0PPSvFHvN7kdNm1VWnluixVbva12pbAnqjrFKfmFI0IHUCAIDeI0QHAJxUhbdVT67Zo469VhsrvLr39S1adMZoTcxL7/VzhMKmDta3aFdNo3bXNGlXTaNq+2jzs0Z/UI01Qe2saYpYT3PaVOJJUUlmioo9bpVkpig/zSWrpf+DdS+d6ACAATC1IEMrdle33270B/Wb93bquxdMUordmsDKhr79dZGjXKK70I85dYRHE/PStP1wY/vaa9sqdNaoHGW5Hf1aIwAA6BtcsQMATqglENJjq3aqNRiOua++NaCH3y7TJZML9YkpRXGFz/5gWLuPNKrscKN21TRqz5Fm+UOxz9GfGn1Bba1q0NaqhvY1l82icblpmpCbrgl5aSrJdPdLqN4YNRN9MI6cAQAMfaeM8GhaYYY2VXjb18q9rfr9+7t189xxsiToHVnJIHpT0ZIuQnTDMPSZGSW67/Wt7Q0JgZCpv208qOvPGNPPVQIAgL7AFTsAoEth09T/rdmjyoauR6iYkl7dWqGyww1adMYYZXfRUeUPhrWrplFl1Y3acbhBe440K2SanR57MhZDKkh3KdvtkHG0hvZ6zLbbtc1+HW70xf0crcGwNlV428MGl82isTlpmpCXpulFHhVlpPSo5mjRG4tGb/wGAEBfsBiGrj9jjB58c5vKva3t65sqvPrr+oP6zIySBFY3dIVNM2acS2lm178jFHvcOmdMrt7t8K6AD/bX6rxxeRqbk9ZvdQIAgL5BiA4A6NI/t1ZofXl9xFqJJ0VpTltE97Yk7axp0n2vb9EpIzzyBcNqDYTaPgdDag2G5W0J9Cg0T7FbVexJUYknRcWZKSrxuFWY4ZLdevLNuEJhUzVNPlU2+lTZ0KrKhlZVeFt1sL6l213vrcGwNld6tbnSq79tPKTxuWk6b1yeZozI7FWHekNr5DgXOtEBAP0lxW7VzXPH6f5l29ToP/4i7vIdVSrMcOmcMbkJrG5oqmnyx7xLr6tO9GMun1aktQdq1RIIta89u+6Avjd/Eu8IAABgkOOKHQDQqQ3l9frH5vKItVSHVV89e6yy3A69sb1Sf990SOEOuXhzIKTVe4/06nnz05wak5OqsTlpGpuTqoJ0V48vLK0WQ/npLuWnu3RKkad9PWy2hesH6o5tWNq2eWl3ZrDvqG7UjupGeVx2nTMmV+eMyZUnJf4u8uhOdGaiAwD6U26qU189e6wefqdMwQ4/vJ/+aJ/yUp2amN/7/U2Gk+gu9DSnTZkn+X0g3WnXZVOK9Nz6A+1r+2qb9f7eIzprdE6/1AkAAPoGV+wAgBiVDa1a+v7uiDEphqSvnDlWOalOSdLCSYWakJeuJat3q6bZ36PnsRhtm3BNyEvT2Jw0jclJVbqz/8eaWAxDeWku5aW5dFpJVvu6tzWgHdWNKjvcoLLDjapoaO3yMepbA/rHlnK9urVcM4sztWBCgUZnp3a7hpgQnXEuAIB+Ni43TV+YNVJ/+GBv+1rYlB5ftUvfmz9J+emuBFY3tMTMQ/ekyOjGi/7njcvTu7sOq7Lx+Ki8Fzcd1MziTLnY6BUAgEGLEB0AEKE1ENJjK3fFvEX5304p1qSoLrXR2an6wUVT9OcP9+rDA3UnfWyLIY3Mcmv80U07x+akKWUQXTBmuOyaVZKlWUeD9WOh+vaqBq07VBcTfEtt4cOHB+r04YE6zS7J0hWnFHc5F/6YQCgc8VZuiU50AMDAOGtUjiq9rfrX9sr2teZASI+8u0NXTB+h00qyGC3SDQfqWiJul55klMsxVouhq2aU6FcrdraveVuD+ue2Cl0xvbhPawQAAH2HK3YAGKLCpilfMCx/MCxfMCR/KNx2O3R8zXf0z8fuO3Zc2/1t64HQsc+mAqG2Gea+qAB9dmmWFkzI77SOFLtVN5wxRrNK6rS9qlFWiyGX3SKnzSqX7fhnt8OmYk/KkOqy6hiqf2ZGiT4+WKd3dh3WrpqmTo9fe6BW6w/V6cKJBVo4qUBOW+dfa2MnYfxAdOADACBJn5o+QpWNrVp/6Pi+J0ea/Vry/h69sqVCl0wu1OzSvg/TTdNUfWtAFsMY0htqm6YZ04lemtW9EF2SphV6NLUgQ5srve1ry8uqdM7oXOWmOfusTgAA0HcI0eNkhkIyQ6GTHwgAnQibploDRzfbDLRtuNnS4c+Rn4/ef3TNdzTcPhaId5xn2p+KM1y6ZkaJFA7rRM84ozBDMwozTvp4Q/XfUJuk04s9Or3YowN1LXp7d7U+OFCrQCjyuxIIm3p1a4VW7anRp6cVaXZJZkwI0dDii7htMaQU69D93gAAhhZD0nWzSvWLRp8OeiNHl1U0tGrpmj16ZUu5LpmYr9klWT3eSDtsmir3tmpHTZN21jRqZ3WTvEdfSM5LdWhyfrom5aVrQm6a3I6h8yJ7fUsg5t1pxenOuH6OXzm9SFurvO17ywTDpv704V594+yxvdq4HAAAxKe7P78N0zQHJoUZ4rxerzwejz78y1+UkZaW6HIAJJg/LDUf/WgNS80hqeXYn8NGhz8r4s++sGRq6FwYpVhMfaPQVPbQbRbrVy0h6YNG6U2vodZw53+vpQ5Tl2ebKu3QWLa9RVpaZWm/nWY19cMSfhwDAAZWfVD642FDB/1d/26SbTM11iVlWk1l2qRMm+SxSh6bZDXafidqDEmNxz6HpIaQoYN+aa9PXf587MiQqRKHNC5FmppiqniQN2NvbZb+7/Dxn+NOw9T/V2oq3uz75SOG3muIPOnsdFOfzOZ3AgAABko4HJZ7xgwVF594rBqd6ACGvbDZFnI3haWm0PHPzWGpKWQc/dy23nz0c8AcOkF4T7kMU9fmEaCfSIpVOtcjzUoz9Ua9tKZBCke9SLLfb+g3FdLcdOmiTFMOS1vA0FGaRQAADDiPTbql0NTmZlPL6w1VBGJ/vzkSNHSkUVLUzzdDpmxG3/xOZMrQfr+03y+9WW/oksywzvP0+mH7zaGo/dSLHIo7QJekBR5T65ulxtDxk1c2GMqzmzoz/QQnAgCAAUeIHqe0U05RRmZmossA0Ac+PFinv6w7qCZ/8IRjSoYKQ5LTZpHDZpHTapHDamm/7bBa5Ty2butwn9Uiu9WQ3WqR3WKR4+ifHTaLCtNdclhJd7sjQ9KXJF3obdXzGw5q6+HGiPtNGVrRIG0NOfXF00oUrGuRasrb78/MTFfGaeMGtmgAAI6aK+ks09SGcq9e3VapA/UtJz3HlKFAP/0C9YbXqrPmTFJu6uBsST+8eo9Uf3ye/OjiPGWcGv+moBmSvnakSf/z7s6IMX0v1Vo0cspYTcojSQcAoL+FQiGFujGohRA9TobVKsM6dOb1Aeia1WpRoz92g8eBciz0dtmtctmsRz9blGK3dlizyGWzKsVuPRqIR4bhbZ/b1mwWQ0YfbwCG+IzIStWt507QxvJ6Pb/hoA43Rs4+r2n265EVu5SZEtnen+6y87MFAJBQVkkzS7M1oyRLGyu8emVLufbVNp/0vO7IcTs0Pi9N43LSNC43Tf5gWFurvNpa1aCd1Y0x+7wEw6Ze2lqpG84Y0yfP39eiX2QoyU7t8c/xsXkZumb2SD25Zm/7WtiUnnh/r743f5Ly0129qhUAAJyYIUnBk2dDhOgAhq00R+//CTQkuR1Wue22ts8Om9x2a9SfY9dS7FY5bJaYDScx9BmGoVNGZGpKYYaWl1Xp5c3lMeFAXUsg4naak5k5AIDBwTAMnVLk0fTCDO2obtTOmkbVNgdU2+zXkaMf/lA45jy7xVC6y650p03pLruy3Q6NzUnVuJw0ZbkdMceXZrm1cFKh/KGwdlU36s2dh7Wx/Hh399r9tVowPl+jslP79euNV5M/qCPNkfNcSjPdvXrMM0bmqMLbqte2VbavNQdC+vV7O/W9+ZPk7oPfWQEAQO/w0xjAsJXmjP0n0GmzKM1hU5rz+Eeqw6b0o5/b14/+2WW3EoSjUzaLRQsnFerUEZn604f7tLO6sctjM1z8OAYADC6GYWhCXromRI0UMU1TLYFQe5ie5mgLzV02S4/eEeewWjS5IEMlmW4t/ucmtQSObxzy1w0Hddt5EwbVO+0O1EV259sshgr7oFv8k9NGqKKhVesPHX8hoarRp9+t3q1vnDNe1p4MXQcAAH2Gq3YAw1Z2qlO3zhsfEYrbmQGOPlaQ7tJt503Qu7uq9beNB+ULxnbv0YkOABgqDMNoe2ddH3dHpzltunhSgf628VD72o7qRm0or9epIzL79Ll6Y39d5CiXYk9KnwTcFsPQojmj9eCb23Www7iYbVUNem7dAX3+tNJePwcAAOg50iIAw5bDatGUggyVZrqV5XYQoKPfWAxD543L078vnKqpBRkx94/IYN4pAAAXjM+PGf3yt40HFQoPni3g90d1opf0cpRLR06bVTfPHaf0qHdLvr3rsF7ZUi6zG5ueAQCA/kFiBADAAMl2O/T1c8bpujmjlJVil8WQzhubp5FZfXcBDgDAUGW3WvTpaSMi1iobfHpvT3WCKooVPc6lJDOlTx8/2+3Q184eJ1tUd/vLm8v15w/3DaoXFAAAGE4Y5wIAwAAyDENnjMzR6aXZCoVN3gEBAEAHs0uztKysMmJsyj82l2tOabZcdmsCK5N8wZCqGnwRa73dVLQzY3JSde3sUVq6Zk/E+nt7alTfGtBXzhwjpy2x3wsAAIYbrtwBAEgAi2EQoAMAEMViGLrylJKItQZfUK9vr0xQRccdrG9Rxz5wiyGN8PRtJ/oxc0Zm67MzShQ9bX1ThVe/fKtM3tZAvzwvAADoHFfvAAAAAIBBY2J+uqYXRu4h8kZZpepa/AmqqE30pqIF6S45+vEF8QvG5+srZ42RPWq0y/66Zj2wfJsqG1r77bkBAEAkQnQAAAAAwKByxSnFEV3YgZCplzeXJ6ye2ma/NpXXR6z1xyiXaKcVZ+mb506Q2xE5vqWm2a8H3tymndWN/V4DAAAgRAcAAAAADDJFGSmaOyY3Ym3VnhodrG/u4oz4BMNh1Tb71RIIyTQ736zzcGOr/rWtQvcv36r/eGWjNld6I+4fiBBdksblpun2CyYpx+2IWG/2h/TwO2V6fXulwl18DQAAoG+wsSgAAAAAYNC5fGqR1uw7In8oLEkyJf3hg736fxdMimuMij8U1qH6Fu2vbdb+uraPQ/WtCh0Nni2G5Lbb5HZY5XbYlOqwqrbZr0PeE49LGZU9MCG61DY65vb5k/Tr93ZqX+3xFxKCYVMvbDiojw7U6kunj1JRRv/MaAcAYLgzzK5edkcEr9crj8ejsrIyZWZmJrocAAAAAEh6r2wpjxnjMqc0S9fNGS3DiN5287iwaeqtHYf13p5qVTa0KtzHV71TCzL09XPGnbCG/uALhvTE6t3aVOGNuc9qGLp0SqEunlQoq2Vg6wIAYKgKhUIKBoMqLi4+4XGE6N1EiA4AAAAAA8sXDOm+N7bqcKMvYv3KU4p14cSCTs8JhsNa+v4efXSwrk9rSbFbdUqRRzOLMzW9yCPLAAfox4TCpv628aCWl1Wps4v5Yk+KvjR7lEqzBq5THgCAoYoQvY8RogMAAADAwKvwtuj+5dvUGgy3rxmSvjFvvKYUZEQc6wuG9Piq3dpSGdup3RPpTptOHZGpmcWZmpCXJptl8GwrtqumUX/8YK8qo15gkNpG1FwwPl8XTSxQhsuegOoAABgaCNH7GCE6AAAAACTG+kN1+u3KXRFrbrtVdyyYrLw0pySp2R/Ur9/bqV01TTHnG2qbK16amaKSTLdKs9wqSncpEDbV7A+qyR86/jkQlGlK43PTNCYnNWEd590RCIX1jy3lemN7Zacja2wWQ2eMzNaFEwtUkO4a+AKRUN7WgKoaWlWQ4VK6kxdTAKAzhOh9jBAdAAAAABKns/noRRkufW/+JPmDYf3vuzt0oL4l4n6H1aLr5ozSlIIMOW3WgSx3QO2rbdYf1+7Vwaiv/xhD0ikjPLpoYoHG5qQNbHFIiI8P1urJNXvlD4VlSBqfl6aZIzI1ozhTmSmORJcHAIMGIXofI0QHAAAAgMQJm6Z+t2q31h2qi1ifVpihw40+VUWNNXE7rPrGOeM1Ojt1AKtMnGA4rH9tq9SrWyoUOsFl/ticVM0bm6vphR65HbYBrBADZcOhOj22aleXG+qOzk5tD9SPvZMDAIYrQvQ+RogOAAAAAInlC4Z0//JtKve2nvC4DJdd35w3XiM8KQNU2eBR2dCqN7ZX6v19RxTsKkVV29z0CbnpOnWER6eOyFSWm+7kZLCl0qvfvLfzhH/3HRVluDS9yKPphZ5BP74IySEQatvfwm4dPHtMYHgjRO9jhOgAAAAAkHjVjT791/KtavaHOr0/x+3QN8+dMOw7bOtbAnpzZ5Xe3VWtlkDn36uOSjPdOnWERxPz0lWa5ZaDgGvI2X64Qb9asUOBUM9inlSHVVMLPTqlyKMpBRlKsSfvCCQMvLBp6s8f7tPqvTUyTSnT7VBeqkO5qU7lpjmVm+pUXppTRRmuQbWJM5IfIXofI0QHAAAAgMFha6VX//vuDkVfzBamu/TNc8cz87mD1kBIK3ZXa/mOKtW1BLp1jtUwVJKZojE5qRqbk6Yx2al0qg9yu2oa9cg7O+Q/2uV7zJmjsjVjRKY+PlinDeX13XpBRWp7p8L43DRNK/RoepGHjWnRa2/tPKy/fLz/pMe5HVadMTJbc0fnDst3E2HgEaL3MUJ0AAAAABg8lpVV6vn1B9tvj8py6+vnjFeakznfnQmFTX14oFZrD9Rqa6W32+M+jslMsavYk6JiT4pGHP2cn+aS1cL4j0TbW9ukh98uU2swMkCfXZqlRXNGt49oCYbD2l7VqI8P1mp9eb0afcFuP0d+mrN97Mu43DT+3hEXXzCkH7+6SQ1x/DcnSaOz3Zo7OlezS7OSenNoJBYheh8jRAcAAACAwcM0Ta3YXa0PD9SqJNOty6YUycX4iW7xBUPaUunV+kP12lher+ZudidHs1kMFWW4NMKTosJ0lwqOfuSmOglZB8iBumb9z9tlMX+HM4szdcMZY7r8ewibpvYcadLG8rb/Bg6dZJ+BjlLsVk0pyND0ogxNLfDwwhVO6p9bK/T3TYd6fL7TZtHskiydMTJbY3PTmN2PPkWI3scI0QEAAAAAySYUNrWzulHrD9WprLpRh+pbYsbkxMtmMZSX5lRhukv56S7lHpt7nOqUJ8VOANZHyr0teuitMjX6I7t7pxdm6Kazx8Y1V/pIk08bK7zaWF6v7Ycbuv1OBUPSmJxUTS9qm6VemO6Swd8vOmjyB/XjVzdFjBKalJeueWNzVd3k0+FGX9vnJr9qm/0nfbw0p02nFHk0c0SmJuans0Epeo0QvY8RogMAAAAAkl1rIKS9tU3aVdOk3TVN2n2kqdtztLvDZjGUczRU97jsctmtSjn64bId/Wy3ypAUMk2Fw2bbZ9NUKGwqbLZ1pXY81mW3KMVuHVabEVY2tOqht7fL2xoZoE/OT9fNc8f1Klj0BUPaVtXQ1qVeUR/zHCeSmWLXmOxUjT76UZrplsM2fP5eEOuFDQf1+vbKiLUfXDhZJZnumGMPN7Zq5Z4ardpb063/7lw2i6YWejRjRNtmuG4H74pA/AjR+xghOgAAAABguAmbpqoaWrW/rkWH6lt0sL5Fh7wt3d6kdCDZrYYynHZ5UuzyuOzKTHF0+PPxtaEe6lY3+fTLt7bH/B2Mz03TN84Z36dfX9g0daCuRRvK67Sx3Kv9dc1xnW8xpBGeFI3OSlVpllsFaU7lp7uU7rTRsT4M1LX4tfjVTQp0eGfD7JIs3XDmmBOeFwqb2lRRr/f21GhTeX233h1jSCrNcmtiXrom5adrbE4qc9TRLYTofYwQHQAAAACANo2+YHuoXtHQqoqGVlU2tMa1WWWipNit8rjawvZj4bonxaFM1/EAPsNlH5Rz3Wub/frlW9tVEzX2YmxOqm6dN77fQ8O6Fr82Hx37srWqQf5Q+OQndSLFblV+mlMF6S7lpzmVm+ZUVopDWW6HPIP0e4/4/fnDfVqxu7r9tsWQ/uPiqcpLc3X7Mepa/Fq994g+PFCrg/Ut3T7PahganZOqiXlpGpuTplFZbjrV0SlC9D5GiA4AAAAAwIk1+oKqPBqoVzS0ts87rmny9zhwTQRDUrrLLo/LpjSnXelOm9KOfqQ7bUpztK0fu+20Wfq9s7q+JaBfvrVdh5t8Eesjs9z61rkTlDLAG+v6Q2GVHW5o35y0to/enWCobSxMltvRHqy3/dmu7KN/dtutdLIPclUNrfrZvzar43j9c8bk6ouzRvb4MasbfVp3qE7rDtVpd01T3Ps35Kc5NSo7VaOy3BqdnapiTwoz1UGI3tcI0QEAAAAA6BnTNNXgC0aE6k3+oFoCIbUGQmoJHv0cCKs12DaD3WIYshpHP1sMWQxDhiH5g+H247u5/2W/s1mMDiF7W7jeFrTbYgN4p12uOEP3htaAHnq7TBUNrRHrxZ4Uffu8CUpNcIetaZqqaGjV7pom7TnSpL21zX2ySW1XHFaLstx2ZbqOjuxJsXd4J4FDmSmD990Ew8WS1bu19kBt+227xdDdl05TZoqjTx7f2xrQ+kP1bZsiH26IGBnTXRZDRzdBTlFRhksF6S4VZbRtiOwYAuH68b0i2vaLCHfYR8KQIafNIofNwmbOJ0GI3scI0QEAAAAAGDxM01QgZKo1GFJLIKRmf0j1rX7VtwRU1xpQfUvg6J/b1lqDg6cTvmPonuY4Hq6nOto2THU7bO0brjpsFv3hg70xoywK01267fwJSnfaE/RVnJgvGNK+2mbtOdKkfbXN7e9MCA7QKx+GpDSnrUPA7oiYj38sfE912AgZ+9iBumbd98bWiLWLJhbo3045cUjZU4FQWLuPNGl7VYO2H27QniNNvXqBzZCU7XYoJ9XZvhFyx89pjv6f6d/QGtCa/Ue0u6Ztc2dfsO0FRl8wLN/Rz935f8lQ22bMTlvbJszHNmXOcB0fXdVxjJXHZR/y+0bEixC9jxGiAwAAAAAwdPmCIdUdDdbrWwOqa/Gr/mjYXnd0rb4loNAQiEny0pz6znkT5UkZnAF6V8KmqSPNflU1+FTV2Db2p6rRp9pmv2pb/AqEBv57bzWMiBDx2IsbqQ6r0hw2pR59oaPjCxt0uJ/Yo+/u0OZKb/vtFLtVP7502oC9Y6I1ENLO6kZtO9yg3TVN2l/X3Kcv3tithjxH3wXRcS+Ftn0WHO1/jrebPRQ2taXSq5V7qrWhvD5h77Rx2SztX0NGh3A9OnCP9x01gxUheh8jRAcAAAAAILmFTVNN/mB7sN7gC6jRF1SDL6jGox9tf25b78kIid7KcTv0nfMnKsvdN2MxBgvTNNXkD6m22a8jR0P1Y+H6keaAapv98rYG+m1ETDwcVkt7oJ5it7aNzbBaZG//MGS3dlwz2u9ztH82ZDUMGUbbqCKLIVksRz93WIu4/+ifu6M7h8UTf3b8vneWJJpHj9hf26xHV+yMuO9T00boksmFcTxb3wqGwzpU36q9R5q0p7ZJe480x4xG6g9uuzUiYM9w2SPeeXJs1JM/FNbqvTVavfeI6lv7Zm+BgeCwWo4G7MffSeN22Dr/bLcp1WGT3WoMuuCdEL2PEaIDAAAAAIBjTNOUPxRuD9iPB+2BiNC90X88eO9tp3Vmil3fOX+iclOdffRVDC3BcFj1LW2B+pEWf/u7CqI/D9TIGJxcutOmH186TU7bwG58ezItgZDK///27ju+pvuP4/j7JpE9jMQmdoLYWqtaWlW7tbX2njXSqv60Rlo6UVRRtPbetJRqSY0aQey9q2K1pEbmPb8/IodLLtGSBK/n4+EhOeOe77353HPufZ/v+Z7Im4qITLgJcuL/f92ISe2mPdWcHCw2Abubk4Nc0zmaw8wk/Jwwze3W9MRpifOdHB5tEJ/cED117zzxH0VFRal79+5auHCh3Nzc9O677+qdd95JctmdO3eqS5cu2rNnj4oWLarx48erTJkyKdxiAAAAAADwNLBYLHJxcpSLk2OyQ+3ouPi7erQnBu0JwfvNmHjdiE0c4/3WjVdvjeWe08dN7crlfWYDdElycnC4NU61/dcgsUf71aiYu4bvuTNoj9E/UXFpolf7065G4WxpLkCXEoaYyZfJU/kyedpMj46L1/l/Em+AHK1L12PM//+6EZ2iQ6ykc7SoZI4Myunjdntc81v/u6RLuKohMVB2TLxiwSFhiCKrkfBcouLiFRVrvfWzVVGx8QlX20TFKjIqVlej4hR5670RE//47xsRZzUUeWvb/5ajxSLnW1d/ODs6JPlz5fx+KuDr+eAHewhPdIjet29fhYWF6ddff9WpU6fUunVr+fv7q1GjRjbLXb9+XbVq1VLz5s01ZcoUjR8/XrVr19axY8fk4eGRSq0HAAAAAADPksTQ/X4h8N3irYbirNY0GUSmRRbL7Zu25vCxv1z8rTDPHBc/KtYcpud6TJyuRcff+j/hd3q3P7xM7s6qlDdTajfjobg4OSp3BnflzuB+zzyrYejKzVv3U7C5l0KMeaLmys3/Hkb7Z3BXhTyZVCZXRrml+/fve0+X5Me+hmEoKs5qvici77iyI9IM3GMVGZVwci81xRuGbt462WhPsez3efP/S0/scC7Xr1+Xr6+vVq5cqSpVqkiShgwZojVr1mjdunU2y37//fcaMmSIjh07JovFIsMwVKhQIX3wwQdq06ZNsrbHcC4AAAAAAADPHsMwFBtv6EZsnKJiE64WiLoV4t2MjVd0nFWxVqti4w3FxlsVY/5uVcytabf/JQwDFBtvVbxhyDASwlmr1ZD11s9PZFB3lwzuzupYPl+SYfTT7mZsvHnFQ+IJmqs3Y23uqfDPrZMziedmPJwd9XzuTCqfJ5Ny+Lil7hN4gJg46x092RP+vx4Tp+sxCVfQ3IhJOAF1IyZe12MTrrBJ6ZruVCGfimdPn6xln/rhXHbt2qXY2FhVrFj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",
      "text/plain": [
       "<Figure size 1500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "patient_start = int(np.sum([len(p_d.data_dynamic) for p_d in patient_data_list[:example_patient_index]]))\n",
    "pred_dict = calc_prediction(pred_model, test_dataset, patient_start, patient_start + len(patient_data.data_dynamic))\n",
    "draw_prediction(patient_data, pred_dict, patient_data.pid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "py38",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
